Age-related cholesterol and colorectal cancer progression: Validating squalene epoxidase for high-risk cases

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dc.contributor.authorSoo Young Jun-
dc.contributor.authorHyang Ran Yoon-
dc.contributor.authorJi Yong Yoon-
dc.contributor.authorJeong Ju Lee-
dc.contributor.authorJ Y Kim-
dc.contributor.authorJ M Kim-
dc.contributor.authorNam-Soon Kim-
dc.date.accessioned2024-07-22T16:32:45Z-
dc.date.available2024-07-22T16:32:45Z-
dc.date.issued2024-
dc.identifier.issn1474-9718-
dc.identifier.urihttps://oak.kribb.re.kr/handle/201005/35490-
dc.description.abstractAs people age, the risk and progression of colorectal cancer (CRC), along with cholesterol levels, tend to increase. Nevertheless, epidemiological studies on serum lipids and CRC have produced conflicting results. We previously demonstrated that the reduction of squalene epoxidase (SQLE) due to accumulated cholesterol within cells accelerates CRC progression through the activation of the β-catenin pathway. This study aimed to investigate the mechanism by which age-related cholesterol accumulation within tissue accelerates CRC progression and to assess the clinical significance of SQLE in older individuals with elevated CRC risk. Using machine learning-based digital image analysis with fluorescence-immunohistochemistry, we assessed SQLE, GSK3βpS9 (GSK3β activity inhibition through serine 9 phosphorylation at GSK3β), p53 wild-type (p53WT), and p53 mutant (p53MT) levels in CRC tissues. Our analysis revealed a significant reduction in SQLE, p53WT, and p53MT and increase in GSK3βpS9 levels, all associated with the substantial accumulation of intra-tissue cholesterol in aged CRCs. Cox analysis underscored the significant influence of SQLE on overall survival and progression-free survival in grade 2-3 CRC patients aged over 50. SQLE and GSK3βpS9 consistently exhibited outstanding prognostic and diagnostic performance, particularly in older individuals. Furthermore, combining SQLE with p53WT, p53MT, and GSK3βpS9 demonstrated a robust diagnostic ability in the older population. In conclusion, we have identified that individuals aged over 50 face an increased risk of CRC progression due to aging-linked cholesterol accumulation within tissue and the subsequent reduction in SQLE levels. This study also provides valuable biomarkers, including SQLE and GSK3βpS9, for older patients at elevated risk of CRC.-
dc.publisherWiley-
dc.titleAge-related cholesterol and colorectal cancer progression: Validating squalene epoxidase for high-risk cases-
dc.title.alternativeAge-related cholesterol and colorectal cancer progression: Validating squalene epoxidase for high-risk cases-
dc.typeArticle-
dc.citation.titleAging Cell-
dc.citation.number7-
dc.citation.endPagee14152-
dc.citation.startPagee14152-
dc.citation.volume23-
dc.contributor.affiliatedAuthorSoo Young Jun-
dc.contributor.affiliatedAuthorHyang Ran Yoon-
dc.contributor.affiliatedAuthorJi Yong Yoon-
dc.contributor.affiliatedAuthorJeong Ju Lee-
dc.contributor.affiliatedAuthorNam-Soon Kim-
dc.contributor.alternativeName전수영-
dc.contributor.alternativeName윤향란-
dc.contributor.alternativeName윤지용-
dc.contributor.alternativeName이정주-
dc.contributor.alternativeName김지연-
dc.contributor.alternativeName김진만-
dc.contributor.alternativeName김남순-
dc.identifier.bibliographicCitationAging Cell, vol. 23, no. 7, pp. e14152-e14152-
dc.identifier.doi10.1111/acel.14152-
dc.subject.keywordAging-
dc.subject.keywordCholesterol-
dc.subject.keywordColorectal cancer-
dc.subject.keywordMachine learning-based digital image analysis combined with fluorescence-immunohistochemistry-
dc.subject.keywordSqualene epoxidase-
dc.subject.localAging-
dc.subject.localaging-
dc.subject.localCholesterol-
dc.subject.localcholesterol-
dc.subject.localColorectal cancer-
dc.subject.localcolorectal cancer-
dc.subject.localColorectal Cancer-
dc.subject.localMachine learning-based digital image analysis combined with fluorescence-immunohistochemistry-
dc.subject.localSqualene epoxidase-
dc.description.journalClassY-
Appears in Collections:
Division of A.I. & Biomedical Research > Immunotherapy Research Center > 1. Journal Articles
Division of A.I. & Biomedical Research > Genomic Medicine Research Center > 1. Journal Articles
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